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A Real Store-Wide Efficiency Alert, From a 40-Week Ledger

· 5 min read
CCLEE
CCLEE

TL;DR​

A real ledger from one store: across 29 historical weeks, store-wide inquiry cost held a stable band of ¥25–31. After new ad solutions launched on June 29, it ran at ¥34–49 for 7 consecutive weeks — then hit ¥69 in week eight. Store-wide decay never announces itself as an incident; it shows up as "every campaign looks fine." So you need a ruler for the sum: a band set by your own history, and an alert on 3 consecutive weeks above it. Had the alarm fired in week three, roughly ¥7,400 of the overspend in the following five weeks would have been avoided.

The situation: every campaign "fine," the sum deteriorating​

Per-campaign reviews read as usual: this campaign's numbers match last month's, that one is stable, the new one is still ramping. All passable.

At the store level: every July week sat above ¥40 per inquiry — in the previous 29 weeks, that line had been crossed exactly once (the Spring Festival week). This post-mortem came out of a store-ledger audit while building AI Operations.

Store-wide inquiry cost across 40 weeks: historical band and the breach

The method: set the band from your own history​

The baseline is not the industry and not a target — it is your own past:

  1. Take weekly store-wide inquiry cost (weekly spend ÷ weekly inquiries) for the past six months
  2. Exclude abnormal weeks: here, two kinds — the Spring Festival week (¥121, spend collapse masquerading as expensiveness) and a 3-week delivery gap in early June (weekly spend ¥90–281, near-dark)
  3. The remaining 26 weeks land between ¥20–41, concentrated in ¥25–31 — that band is "normal"
  4. Alert condition: 3+ consecutive weeks above the band's top, with spend not shrinking (cost rising because spend is collapsing is a different problem)

(Technical note: why "consecutive 3 weeks" rather than any single week — in the 29 historical weeks, single-week breaches happened 4 times, all noise; consecutive breaches happened zero times. The baseline tells you how strict the threshold should be.)

The full post-mortem​

  • June 8–22: a 3-week gap. Weekly spend fell from ~¥1,900 to ¥90–281 — near-dark
  • June 29: new ad solutions launched (the solution-switch details and data are in Same Product, 4× the Inquiry Cost)
  • From June 29: 7 consecutive weeks above the band — ¥46 / 43 / 40 / 43 / 40 / 49 / 34, every one above the historical top of ¥31
  • Week of August 17: ¥69, as spend spiked to ¥5,210 without inquiries following

A gap-and-restart is not a return to the old normal: the environment changed and the solutions changed — the old cost level no longer applies. That is exactly the kind of account-level shift single-campaign views cannot see, and only the store line exposes.

What it's worth: the overspend ledger​

The 7 breached weeks (Jun 29 – Aug 10) spent ¥24,699 for 592 inquiries — ¥41.7 each. At the historical level (¥28), the same inquiries would have cost ¥16,576: about ¥8,100 of overspend in 7 weeks. Had the alarm fired in week three and intervention started in week four, roughly ¥7,400 of the last five weeks' overspend was avoidable. That is the price of the ruler: set it once, watch one number.

Disciplines for operators​

  1. The band must come from your own history: at least six months of weekly data, abnormal weeks excluded. A three-week average as a ruler is worse than no ruler.
  2. 3 consecutive weeks above the top, with spend holding, = alert: single weeks are noise; consecutive weeks are structure.
  3. After an alert, hunt the common cause first: solution switches, gap-and-restarts, category-wide competition shifts are account-level events — fixing campaigns one by one treats symptoms.
  4. The cost numbers themselves must settle first: weekly data carries a settlement tail; the discipline is in Is 16 Days Enough for Marketplace Ad Data? We Re-Collected 5 Weeks to Find Out.

One line to remember

Set the band from history (six months, abnormal weeks out); 3 consecutive weeks above it = alert. Alerts trigger a hunt for account-level causes; actions stay at campaign level.

FAQ​

What signals a store-wide ads efficiency decline?​

Weekly inquiry cost above your own historical band for 3+ consecutive weeks while spend holds — each campaign can look passable alone while the sum is sinking.

How do I set the 'normal band'?​

Take your own half-year of weekly inquiry costs, exclude abnormal weeks (holidays, delivery gaps), and use the median ±10% as the band. Stores with thin history should accumulate first.

What is the first move after an alert?​

Hunt for an account-level cause before touching campaigns: solution switches, gap-and-restart episodes — store-wide breaches are usually account-level events.

That "band from history, watch the store" alerting logic is built into AI Operations — LLM-powered analysis that automatically surfaces market trends, user behavior, and sales data to drive strategy. Efficiency decay should not wait for a quarterly review to be discovered.

CCLEE

Independent developer, 24 years in e-commerce, focused on grounding AI in real business scenarios.

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